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    Verification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models

    Source: Journal of Hydrologic Engineering:;2020:;Volume ( 025 ):;issue: 003
    Author:
    Kang Xie
    ,
    Pan Liu
    ,
    Jianyun Zhang
    ,
    Dominic A. Libera
    ,
    Guoqing Wang
    ,
    Zejun Li
    ,
    Dingbao Wang
    DOI: 10.1061/(ASCE)HE.1943-5584.0001887
    Publisher: ASCE
    Abstract: The Soil Conservation Service Curve Number (SCS-CN) method is widely used in conceptual rainfall-runoff models for describing the runoff response with a curve, which is a function of the cumulative storm rainfall and antecedent wetness conditions. To improve the SCS-CN method, a new distribution function was recently proposed to unify the surface runoff modeling of the SCS-CN method and probability-distributed functions in the variable infiltration capacity (VIC) and Xin’anjiang models. This study aims to verify the new distribution function in a conceptual rainfall-runoff model and in the Soil and Water Assessment Tool (SWAT) by using real catchments. The Xunhe River basin in China and other basins in the United States were used as case studies. Results show that more observed variability in streamflow is captured when using the new spatial distribution function of soil water storage capacity in the conceptual runoff model. Specifically, there is a 9.8% average increase in the Nash-Sutcliffe efficiency (NSE), while simultaneously reducing the bias and mean relative absolute error (MRAE). When using the new distribution in SWAT, the model is able to better estimate the observed streamflow as indicated by higher NSE values for most of the basins. Akaike information criterion (AIC) is used for validating the goodness-of-fit when the number of parameters and model structure change. Further findings suggest that the estimated variance is more sensitive to the value of the new shape parameter a when soil water content is low in the early stage of rainfall. Therefore, the proposed new distribution function is shown to be effective in improving the accuracy of simulating streamflow for both conceptual and SWAT models.
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      Verification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4265831
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    contributor authorKang Xie
    contributor authorPan Liu
    contributor authorJianyun Zhang
    contributor authorDominic A. Libera
    contributor authorGuoqing Wang
    contributor authorZejun Li
    contributor authorDingbao Wang
    date accessioned2022-01-30T19:42:28Z
    date available2022-01-30T19:42:28Z
    date issued2020
    identifier other%28ASCE%29HE.1943-5584.0001887.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265831
    description abstractThe Soil Conservation Service Curve Number (SCS-CN) method is widely used in conceptual rainfall-runoff models for describing the runoff response with a curve, which is a function of the cumulative storm rainfall and antecedent wetness conditions. To improve the SCS-CN method, a new distribution function was recently proposed to unify the surface runoff modeling of the SCS-CN method and probability-distributed functions in the variable infiltration capacity (VIC) and Xin’anjiang models. This study aims to verify the new distribution function in a conceptual rainfall-runoff model and in the Soil and Water Assessment Tool (SWAT) by using real catchments. The Xunhe River basin in China and other basins in the United States were used as case studies. Results show that more observed variability in streamflow is captured when using the new spatial distribution function of soil water storage capacity in the conceptual runoff model. Specifically, there is a 9.8% average increase in the Nash-Sutcliffe efficiency (NSE), while simultaneously reducing the bias and mean relative absolute error (MRAE). When using the new distribution in SWAT, the model is able to better estimate the observed streamflow as indicated by higher NSE values for most of the basins. Akaike information criterion (AIC) is used for validating the goodness-of-fit when the number of parameters and model structure change. Further findings suggest that the estimated variance is more sensitive to the value of the new shape parameter a when soil water content is low in the early stage of rainfall. Therefore, the proposed new distribution function is shown to be effective in improving the accuracy of simulating streamflow for both conceptual and SWAT models.
    publisherASCE
    titleVerification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models
    typeJournal Paper
    journal volume25
    journal issue3
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0001887
    page04020001
    treeJournal of Hydrologic Engineering:;2020:;Volume ( 025 ):;issue: 003
    contenttypeFulltext
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